class_docstr: 🤗 Constructor for the image classifier trainer
class_docstr_tok: ["\ud83e\udd17","Constructor","for","the","image","classifier","trainer"]
code: def __getOutputPath(self):
      path = os.path.join(
          self.output_dir,
          self.model_name.upper()
          + "/"
          + str(self.max_epochs)
          + "_"
          + datetime.today().strftime("%Y-%m-%d-%H-%M-%S"),
      )
  
      # Create the full path if doesn't exist yet
      if not os.path.isdir(path):
          os.makedirs(path)
  
      return path
  
file_path: HugsVision/hugsvision/nnet/VisionClassifierTrainer.py
imports: import os
  from datetime import datetime
  import torch
  from sklearn import metrics
  from sklearn.metrics import precision_recall_fscore_support
  from transformers import Trainer
  from transformers.training_args import TrainingArguments
  from transformers.feature_extraction_utils import FeatureExtractionMixin
  from tqdm import tqdm
  from PIL import Image
  from hugsvision.dataio.ImageClassificationCollator import ImageClassificationCollator
label_desc: Use image node_id 3 for calling the VisionClassifierTrainer obj's underlying member method code with example usage: obj.__getOutputPath() and returns: path